Quantitative Researcher

Tasks

• Design and automation of risk, parity, and macro-quant investment strategies across various financial markets, within the dedicated China macro team.
• Taking responsibility for the entire investment lifecycle—from alpha generation and portfolio construction to trade execution and risk management.
• Tracking and executing signals based on multiple proprietary data sets, geopolitical signals, and quantitative trading strategies, such as:
  • Alpha Generation & Strategy Development: Using insights to identify mispricings and divergences across cross-border equity, fixed-income, credit, and currency asset classes in the Chinese market.
  • Risk Optimization: Effective risk management across multiple strategies and asset classes; determining appropriate position sizes across various assets and time horizons.
  • Portfolio management and optimization of the investment strategy, including the definition of a complex set of multi-asset, dynamic leverage, diversification, and rebalancing strategies. This involves robust risk modeling and quantitative optimization.
  • Strategic Data-Driven Analysis: Using data-driven, systematic analysis and quantitative integration to build a deep understanding of various regional and global factors affecting the Chinese asset market.
  • Using data science insights to contribute to risk management, leverage across portfolios, and systematic monitoring of portfolio risk factors, employing statistical methods to achieve a better risk-return profile.
  • Data Science: Collaboration in data science using purpose-built, internal data platforms to collect, process, and analyze data from internal and external sources.
  • Monitoring: Establish and monitor systematic risk triggers to identify risk control opportunities, improve portfolio stability, and enhance the efficiency of the risk management process.
  • Research: Support for the development of the risk management framework and the continuous improvement of the risk management process.

Requirements

• Advanced degrees in computer science, statistics, mathematics, finance/economics, or related quantitative fields (a Ph.D. is preferred but not required).
• Extensive practical experience in developing and implementing market, customer, product, and trading strategies.
• A strong commitment to profitability and return on investment, as well as the ability to contribute to strategic decisions regarding customers.
• Active interest in developing skills with a focus on data science, machine learning, and AI.
• A solid understanding of financial markets and products, as well as the mechanisms of global trade and the derivatives market.
• An analytical and systematic approach, working from first principles, strong mathematical skills, and quantitative programming skills.
• Collaboration and cross-functional skills, including strong communication and delegation skills.
• Business acumen and a strong work ethic, combined with a passion for customer service.
• Knowledge of advanced mathematical and statistical concepts and their application to real-world quantitative trading.
• Strong programming skills (e.g., Python, C++, Java) and experience with large datasets.
• Understanding a quantitative overlay that spans multiple asset classes, multiple strategies, and multiple time horizons.
• Excellent customer service skills and the ability to work with both internal and external stakeholders.